👅 AI Tongue Enables Robots to Taste Food

Welcome AI & Healthcare enthusiasts!

As AI and robotics innovations accelerate, we're witnessing breakthroughs almost daily. Case in point: robots just learned to taste. Yes, an AI-powered electronic tongue can now tell the difference between Coke and Pepsi better than humans.

Meanwhile, Suki's $70M funding signals a fierce battle with Abridge for AI supremacy in clinics documentation. Microsoft also unveiled new AI tools to solidify its place as a major player in Healthcare. And did I mention most older adults still don't trust AI for health advice?

Let’s dive in!

Victor

TODAY’S MENU

• This Electronic Tongue Could Help Robots Taste Food Like Humans

• Most Older Adults Don’t Trust AI-Generated Health Information

• Suki Raised $70 Million to Beat out Rival Abridge

• Microsoft Launches New AI Tools for Healthcare

• Researchers Use AI to Find Non-Opioid Pain Relief Options

• Everything Else You Should Know this Week

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  Read time: under 6 minutes

FUTURE IS NOW

This Electronic Tongue Could Help Robots Taste Food Like Humans

Scientists at Penn State just created an AI-powered 'electronic tongue' that can identify subtle differences in liquids, detect food spoilage, and gain broader insights into AI’s decision-making processes.

Key Details:

• The electronic tongue combines a special sensor with an AI modeled after the human brain's taste center, enabling it to ‘taste’ liquids.

• The tongue can ID differences in similar liquids like watered-down milk, sodas (even Coca from Pepsi), coffee, and spoiled fruit juices with over 80% accuracy in about a minute.

• When the AI was allowed to interpret the sensor data on its own terms, it achieved over 95% accuracy in identifying the samples.

• Researchers also used methods to examine the AI's thought process, helping understand how it weighs different pieces of information to make decisions.

Why it matters: AI achieved some serious sensory upgrades this year, from vision and hearing capabilities to humanoid robotic touch — and now, add taste to the list. The AI epicure could one day help scientists develop better-tasting foods — or detect problems with ingredients before they hit store shelves.

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POLL

Most Older Adults Don’t Trust AI-Generated Health Information

A new poll from the University of Michigan and AARP reveals a trust gap among adults over 50 regarding AI-generated health information. Many older adults express concerns about their ability to discern reliable health content online, especially as AI-driven platforms proliferate. This is especially critical for those with health conditions or disabilities who may be more dependent on accurate medical information.

Key Numbers:

• 74% of adults 50+ distrust AI-generated health content.

• 20% struggle to spot health misinformation.

• Only 32% say it’s easy to find accurate health information online.

• 70% trust healthcare providers, but only 36% trust commercial health sites like WebMD.

Why it matters: As AI increasingly enters healthcare, there’s a clear need for trusted health institutions to step up. Older adults, especially those in vulnerable health conditions, require access to reliable, easy-to-understand health resources that they can trust.

AMBIANT AI

Suki Raised $70 Million for Its Healthcare AI Assistant to Beat Out Rival Abridge

Suki, the AI-driven voice assistant for clinicians, just raised $70 million to expand its capabilities and partnerships. Founded in 2017, the company has rapidly grown, partnering with major health systems, including MedStar Health. Suki Assistant, designed to streamline administrative tasks like clinical documentation, is now available to thousands of MedStar clinicians.

Key details:

• Suki Assistant uses voice and generative AI to create clinical notes, cutting documentation time by up to 72%.

• Already adopted by over a dozen health systems, Suki integrates with EHR platforms like Epic and Cerner.

• The company aims to enhance Suki’s features for broader administrative and clinical support, including pre-visit summaries and order entries.

Why it matters: Suki’s latest funding highlights its push to dominate the ambient AI and clinical documentation space, facing stiff competition from Abridge. Both are scaling rapidly, seeking to revolutionize AI-driven healthcare workflows, with Abridge valued at $2.5B post-funding.

MICROSOFT

Microsoft Launches New AI Tools for Healthcare

Microsoft ramped up its healthcare AI push with the introduction of new medical imaging foundation models, a healthcare agent service in Copilot Studio, and a deeper collaboration with Epic centered around nursing workflows.

Key details:

• Multimodal AI Models: Microsoft’s new medical imaging models, available through Azure AI Studio, can process a variety of data types, including medical images, clinical records, and genomic data. These models are designed to help healthcare organizations develop more accurate diagnostics. Providence Health is testing this technology to improve cancer subtyping and mutation prediction using whole-slide pathology images.

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• Healthcare AI Agents: The new healthcare agent service in Copilot Studio allows organizations to create AI agents for tasks like clinical trial matching and patient triaging. These agents offer transparency by citing clinical evidence, setting Microsoft apart from competitors. Early adopters like Cleveland Clinic are already using these tools to improve patient experiences.

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• Nurse Documentation Expansion: In collaboration with Epic, Microsoft is enhancing its DAX Copilot tool to assist nurses in reducing time spent on documentation. This feature, designed with input from major health systems like Stanford and Northwestern, aims to address the critical shortage of nurses by automating flowsheet documentation.

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Why It Matters: Microsoft’s entrance into this space isn’t just about offering new tools; it’s about scale and integration. Its Azure platform, combined with Nuance’s speech-to-text AI, puts Microsoft in a unique position to dominate the healthcare AI landscape, especially as regulatory compliance becomes a key differentiator.

DRUG DISCOVERY

Researchers Use AI to Find Non-Opioid Pain Relief Options

Researchers at Cleveland Clinic and IBM have developed an AI model that could uncover new non-addictive treatments for pain by predicting how drugs and gut microbes interact with pain receptors.

Key Details:

• LISA-CPI analyzes the molecular structure of compounds and the 3D shape of pain receptors to predict how they will interact.

• The AI model identified FDA-approved drugs like methylergometrine, which could potentially be repurposed to target specific receptors involved in pain.

• LISA-CPI also found gut microbes that might have beneficial interactions with pain receptors.

• This method could accelerate drug discovery for pain relief by more effectively screening potential compounds.

Why it matters: With the ongoing opioid crisis, the need for non-addictive pain treatments is urgent. This AI-driven approach offers a promising avenue for discovering new pain management solutions while avoiding the pitfalls of opioid use.

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Must-Read AI Healthcare News This Week

DeepMind’s AlphaFold2 creators win Nobel Prize for chemistry-focused AI: CEO Demis Hassabis and John Jumper receive the Nobel for their breakthrough AI platform, used by over 2 million researchers to accelerate cancer treatments, vaccine development, and material discovery.

Basecamp Research draws $60M to build a ‘GPT for biology’: The London startup aims to create an AI that uncovers biological insights beyond human reach by gathering biodiversity data and surpassing current models like AlphaFold 2.

70,500 new RNA viruses uncovered: A study from Sun Yat-sen University used Meta’s ESMFold tool to identify thousands of RNA viruses from environmental data.

Lung cancer diagnosis gets 10x faster with new blood test: A microchip captures cancer exosomes, offering quicker, more sensitive detection through a simple blood draw.

Soft ‘Finger’ robot mimics human touch for early disease detection: Chinese researchers unveil a soft robotic finger capable of detecting tumors and taking pulses, offering a gentler, more precise method for diagnosing diseases like cancer.

CERN trains AI models to revolutionize cancer treatment: By applying particle accelerator technology, CERN develops AI tools for early cancer detection, stroke monitoring, and improved access to radiotherapy, especially in underserved regions.

Thanks for reading!